How is ExoView different from NTA?

NTA is commonly used for overall particle concentration and size distribution based on motion and scattering. ExoView adds immunocapture-based specificity and single-particle phenotyping, enabling subpopulation-level quantification and 3-color colocalization for co-expression and cargo-positive estimation (design-dependent).

Do I need to purify exosomes before ExoView analysis?

Many studies can be designed with reduced over-processing by targeting EV subsets via immunocapture. The best approach depends on matrix, abundance, and goals. We confirm recommended pre-processing and controls during feasibility planning.

What markers can you analyze?

Standard designs often include CD9/CD63/CD81. Additional targets can be included in capture and/or fluorescence panels upon request, subject to feasibility and control design.

Can ExoView estimate cargo-positive fractions for engineered exosomes?

Yes—when the study includes appropriate labeling/staining and controls, colocalization can estimate cargo-positive fractions and their association with surface phenotypes (design-dependent).

What is the minimum sample volume?

ExoView workflows can be micro-volume. Typical inputs are often around ~35 µL per assay in common implementations, but exact requirements depend on matrix, abundance, and panel design.

ExoView Exosome / EV Profiling Service

Why Choose ExoView for Exosome Immunophenotyping and Colocalization

Resolve EV heterogeneity with single-particle readouts

EV samples are heterogeneous. Bulk averages can obscure rare or biologically important subsets. ExoView provides subpopulation-level quantification so you can link signals to specific EV subsets.

Improve interpretability in complex biofluids

Plasma/serum and other biofluids contain abundant background particles. With immunocapture-based specificity, ExoView focuses analysis on the EV subsets you care about and supports research workflows that reduce bias from over-processing (design-dependent).

Quantify co-expression and cargo-positive fractions for engineered exosomes

Therapeutics and engineering teams often need the fraction of vesicles that are truly marker-positive or cargo-positive. 3-color fluorescence colocalization helps estimate these fractions directly when appropriate staining/labeling and controls are used.

Key Capabilities and Typical Specs (ExoView / SP-IRIS)

Capabilities and ranges can vary by sample type, panel design, and QC requirements. We confirm feasibility and recommended controls before project start.

Item	Typical capability / note
Single-particle sizing (typical)	Small EV range; commonly cited detection from ~50 nm in many research implementations (project-dependent)
Sample input	Micro-volume workflows (often ~35 µL per assay in common implementations; project-dependent)
Immunophenotyping	Antibody-capture EV subset quantification (CD9/CD63/CD81; custom targets upon request)
Colocalization	Up to 3-color fluorescence colocalization for co-expression and cargo-positive estimation (design-dependent)
Multi-capture arrays	Commonly up to ~6 capture antibodies per chip (design-dependent)
Automation / throughput	Options for automated multi-sample handling (commonly up to ~9 samples per run; platform-dependent)
Typical workflow duration	Often ~2 days (capture + staining) with rapid per-chip readout; depends on design/QC
Data package	Standardized PDF report + tables (CSV/XLSX) + publication-ready image exports

Optional add-ons: orthogonal characterization (NTA, TEM, WB), EV multi-omics, and functional studies are available.

Use Cases: Biofluid EV Biomarkers, Engineered Exosomes, and Research QC Trending

Biofluid biomarker discovery and validation

Quantify EV subpopulations in plasma/serum/urine/CSF and compare cohorts or timepoints
Generate colocalization matrices to support marker specificity

Common add-ons: TEM/WB validation, targeted EV proteomics, downstream statistics

Engineered exosomes and therapeutics development

Estimate cargo-positive fractions (labeling/staining design-dependent)
Verify surface ligand expression and multi-marker co-expression on the same vesicle
Support MOA hypotheses with subpopulation shifts and colocalization evidence

Common add-ons: intravesicular staining add-on, uptake assays, in-vitro functional readouts

Process development and QC trending (research)

Track batch-to-batch consistency of marker-defined EV subsets
Monitor subpopulation proportions as research-stage quality proxies
Standardize panels for longitudinal trending

Common add-ons: stability study designs, supplementary orthogonal characterization

Service Workflow: From Study Design to Report

Deep navy workflow of ExoView SP-IRIS single-particle exosome/EV profiling with design, QC, imaging, and reporting steps. End-to-end workflow for ExoView SP-IRIS single-particle EV profiling, from study design to standardized reporting.

Study Design & Controls (Included Feasibility Guidance)

We provide feasibility guidance to align the capture/marker design, controls, and outputs to your research question before you ship samples.

Panel strategy (capture + fluorescence)

Capture design: standard tetraspanins (CD9/CD63/CD81) and/or custom targets (upon request)
Fluorescence design: up to 3 channels for marker co-expression and cargo-associated signals (design-dependent)
Comparability: fixed panel across groups/timepoints for biomarker and trending studies

Control framework (recommended)

Control / design element	Purpose
Negative and/or isotype controls	Assess non-specific binding and background signals
Blank spots / background checks (as applicable)	Evaluate surface/background contributions to signal
Process controls (reference samples)	Support longitudinal studies and batch trending comparability
Replicate / randomization guidance	Minimize batch effects and improve interpretability

Goal-to-module mapping

Your primary goal	Recommended approach
Subtype profiling / co-expression / colocalization	ExoView single-particle profiling
Baseline concentration / size screening	Optional NTA add-on
Morphology confirmation	Optional TEM add-on
Marker verification	Optional WB add-on
Discovery / mechanism	Optional EV omics and/or functional studies

Send your sample type, approximate abundance (if known), target markers, and study design (groups/timepoints). We will propose a panel, controls, deliverables, estimated turnaround time, and quote.

Sample Types and Requirements for ExoView Exosome / EV Profiling

Sample Type	Recommended Submission	Typical Minimum Volume*	Key Notes (To Avoid Failure)
Cell culture supernatant	Clarified supernatant in low-bind tubes	35 µL per assay	Record media type/serum use; avoid repeated freeze–thaw cycles.
Plasma	Frozen aliquots on dry ice	35 µL per assay	Report anticoagulant (EDTA, citrate, heparin); avoid hemolysis and lipemia.
Serum	Frozen aliquots on dry ice	35 µL per assay	Note clotting conditions; avoid hemolyzed samples.
Urine	Frozen aliquots on dry ice	35 µL per assay	Record collection time; clarify to reduce debris if possible.
CSF	Frozen aliquots on dry ice	35 µL per assay	Low abundance; provide metadata and controls for better interpretability.
Other biofluids	Case-by-case review	35 µL per assay	Feasibility confirmed during feasibility planning.

*Typical micro-volume ExoView assays are often designed around 35 µL per assay. Exact requirements depend on matrix, abundance, and study design.

Immunocapture and Imaging (What Happens on the Platform)

Immunocapture on antibody microarray

EV subsets are captured on-chip using antibody spots (commonly including CD9/CD63/CD81 and optional custom targets). This step enriches target populations and supports subset-specific readouts.

SP-IRIS interferometric imaging (label-free)

We perform interferometric imaging to identify and quantify captured single particles prior to fluorescence. This establishes a robust base for downstream phenotyping and QC.

Fluorescence staining (up to 3-color; design-dependent)

When the research question requires marker co-expression or cargo-associated signals, we apply up to 3 fluorescence channels and quantify colocalization at the single-particle level.

Results You Receive: Single-Particle EV Readouts and Publication-Ready Visuals

Core ExoView readouts (design-dependent)

Single-particle counts and size distributions (for captured EV populations)
Marker positivity per capture spot and/or per particle
3-color colocalization statistics and subpopulation proportions
Representative interferometric and fluorescence overlays
QC notes and control interpretation aligned to the agreed design

Deliverables for analysis and reporting

Standardized PDF report with methods, controls, and interpretation notes
Exportable tables (CSV/XLSX) for statistics and cohort comparisons
Publication-ready images/plots (high-resolution exports)
Optional: figure pack and methods text for publications/grants

Multi-panel ExoView SP-IRIS single-particle EV image showing label-free field and 3-color marker colocalization overlays. Label-free SP-IRIS imaging plus 3-color fluorescence colocalization for single-particle exosome immunophenotyping.

ExoView SP-IRIS charts of single-particle EV size distributions and captured particle counts for CD9/CD63/CD81 subsets. ExoView single-particle EV sizing and particle counts across immunocaptured exosome marker subsets.

ExoView single-particle exosome colocalization matrix heatmap with stacked bars showing EV subpopulation proportions. Single-particle colocalization heatmap and EV subpopulation proportions from ExoView exosome profiling.

ExoView SP-IRIS single-particle EV plots showing batch trending, counts, and feature clustering for research QC. ExoView single-particle EV batch trending for research QC consistency and subpopulation stability.

Assay Options and Packages (Tetraspanins, Custom Targets, Cargo Add-Ons)

We tailor capture and marker panels to match your biological question while maintaining a control framework that supports comparability across groups and timepoints.

Package	Best for	Typical outputs
Standard EV immunophenotyping (tetraspanin panel)	Baseline EV subset profiling (e.g., CD9/CD63/CD81-defined subpopulations)	Subpopulation proportions, colocalization summaries, representative images
Target marker profiling (custom; upon request)	Enrichment/profiling of specific EV sources or functional subsets	Target-focused positivity and colocalization statistics; panel feasibility confirmed case-by-case
Cargo / intravesicular marker add-on (design-dependent)	Engineered exosomes, cargo-positive fraction estimation, MOA support	Cargo-associated signal positivity, cargo–surface phenotype colocalization, QC notes

Client-Published Surfaceome Case Highlights

Case 1: Tetraspanin Heterogeneity and Capture Bias in Single-EV Profiling (ExoView / SP-IRIS)

Objective: Reveal how EV tetraspanin heterogeneity (CD9/CD63/CD81) impacts single-vesicle profiling and biomarker sensitivity, and evaluate capture-related bias in multiplex assays.

Method: SP-IRIS single-particle capture + 3-color immunofluorescence on ExoView (tetraspanin microarray capture), benchmarking against NTA/TEM/flow-based approaches; multiplex co-localization analysis across EV sources and isolation methods.

Result: Demonstrated that tetraspanins are unevenly distributed across single EVs and that capture choice can bias the apparent multiplex profile—materially affecting sensitivity to tumor-associated surface markers; supports using single-particle phenotyping (not bulk averages) for rigorous EV biomarker/assay development.

DOI: 10.1186/s12951-021-00987-1

Case 2: Plasma sEV Profiling + ExoView Marker Imaging to Support EV-miRNA Biomarker Work (SP-IRIS / ExoView R100)

Objective: Characterize plasma small extracellular vesicles (sEVs) and integrate EV profiling with downstream sEV-miRNA analysis in an oncology response-prediction research workflow.

Method: Plasma sEV isolation + orthogonal characterization (NTA, TEM) + ExoView R100 (SP-IRIS) single-particle imaging for CD63/CD81/CD9 marker visualization and phenotyping; paired with small RNA-seq and bioinformatic analysis of sEV miRNAs.

Result: Provided an example of how single-particle EV marker confirmation (ExoView) strengthens confidence in EV identity/quality before sequencing-driven biomarker analysis; supports positioning ExoView as the "front-end QC + phenotyping gate" for complex plasma EV biomarker projects (research use).

DOI: 10.1186/s12645-024-00273-3

Single-Particle Exosome / EV Profiling with ExoView

Technical Overview: ExoView (SP-IRIS) Single-Particle EV Profiling